Drive Time Analysis
Drive time analysis calculates the geographic area reachable from a location within specified travel time thresholds, accounting for road networks and traffic conditions. It is a more accurate alternative to simple radius buffers for defining trade areas and measuring accessibility.
Drive time analysis is a network-based spatial analysis technique that determines the area accessible from a given point within a set of time thresholds—such as 5, 10, 15, or 20 minutes—by car, truck, or other vehicle. Unlike simple distance buffers that draw circles around a location, drive time analysis follows actual road networks and incorporates speed limits, road classifications, turn restrictions, and optionally real-time or historical traffic data to produce realistic accessibility zones called isochrones.
How It Works
Drive time analysis uses a routable road network dataset and a shortest-path algorithm (typically Dijkstra's or A*) to calculate the maximum extent reachable from an origin point within each time threshold. The algorithm traverses the network graph, accumulating travel time along each road segment based on its speed profile, until the time budget is exhausted. The resulting isochroneIsochroneAn isochrone is a line or polygon on a map connecting all points reachable from a given location within a specified t... polygon encloses all reachable network nodes and the areas between them. Modern implementations support multiple travel modes (driving, walking, cycling, public transit) and can incorporate time-of-day traffic patterns to produce peak-hour versus off-peak accessibility zones.
Applications
Drive time analysis is foundational to retail site selectionSite SelectionSite selection is the analytical process of evaluating and choosing optimal physical locations for new stores, facili..., where it defines realistic trade areas that reflect how far customers are willing to drive. A convenience store might evaluate 5-minute drive-time zones, while a regional shopping center analyzes 20- or 30-minute zones. Healthcare planners use drive time analysis to assess patient access to hospitals and emergency services. Logistics firms use it to define delivery zones and optimize last-mile routing. Emergency management agencies evaluate evacuation times and response coverage.
Advantages
Drive time analysis produces dramatically more accurate trade areas than distance rings, especially in areas with natural barriers (rivers, mountains), sparse road networks, or heavy traffic congestion. Two locations equidistant in straight-line distance can have vastly different drive-time accessibility, and only network-based analysis captures this reality.
Challenges
Accuracy depends on the quality and currency of the underlying road network data, including speed profiles and traffic information. Computational requirements increase with network size and the number of origin points analyzed. Real-time traffic integration adds complexity and cost but significantly improves accuracy for peak-hour analyses. Drive time analysis is an essential tool in the location intelligence toolkit. By grounding accessibility in real-world travel conditions rather than abstract distances, it ensures that trade area definitions, site evaluations, and service coverage assessments reflect the actual experience of customers and users.
Code-Beispiele
import requests
# Generate drive-time polygons
response = requests.post(
"https://api.openrouteservice.org/v2/isochrones/driving-car",
headers={"Authorization": ORS_API_KEY},
json={
"locations": [[13.405, 52.52]],
"range": [300, 600, 900], # 5, 10, 15 min
"range_type": "time"
}
)
isochrones = response.json()
for feat in isochrones["features"]:
mins = feat["properties"]["value"] / 60
print(f"{mins:.0f}-min zone: "
f"{len(feat['geometry']['coordinates'][0])} vertices")Verwandte Mapular-Lösungen
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